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38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
import pandas as pd
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import os
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# Preprocess data
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vote_counter = -1
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data = pd.DataFrame()
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name_column = 'Bezeichnung'
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column_to_filename = {}
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voting_features = ['ja', 'nein', 'Enthaltung', 'ungültig']
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for dirname, _, filenames in os.walk('./de/csv'):
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for filename in filenames:
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vote_counter += 1
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print(os.path.join(dirname, filename))
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df = pd.read_csv(os.path.join(dirname, filename))
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# Give each voting behaviour type an identifier from 0 to len(voting_features) - 1
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for i, feature in enumerate(voting_features):
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df[feature] *= i
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vote_column_name = f'vote_{vote_counter}'
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# Map column name of vote to filename -> allows retrieving what the vote was about
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column_to_filename[vote_column_name] = filename
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# add feature for the vote
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df[vote_column_name] = df[voting_features].sum(axis=1)
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if data.empty:
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# if first file that is loaded set data equal to data from first file
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data = df[[name_column, vote_column_name]]
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else:
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# merge data with already loaded data
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data = data.merge(df[[name_column, vote_column_name]], on=name_column)
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print(column_to_filename)
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print(data)
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